p-variation of strong Markov processes
Abstract
Let t, t∈[0,T], be a strong Markov process with values in a complete separable metric space (X,) and with transition probability function Ps,t(x,dy), 0 s t T, x∈ X. For any h∈[0,T] and a>0, consider the function α(h,a)=supPs,t(x,y:(x,y) a):x∈ X,0 s t (s+h) T. It is shown that a certain growth condition on α(h,a), as a0 and h stays fixed, implies the almost sure boundedness of the p-variation of t, where p depends on the rate of growth.
0
Turn this paper into a full lesson
ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.